Fig. 1 | Scientific Reports

Fig. 1

From: Integrative bioinformatics and machine learning identify key crosstalk genes and immune interactions in head and neck cancer and Hodgkin lymphoma

Fig. 1

Flowchart depicting study design. DEGs were identified in HNSCC (TCGA) using DESeq2, while key-module genes were selected via WGCNA in HL (GSE12453). The intersection of DEGs and key-module genes underwent enrichment analysis (GO, DO, KEGG). Six machine learning algorithms (LASSO, RF, SVM + RF) identified candidate genes, with final hub genes selected based on survival analysis and ROC. Validation was conducted using HPA, GTEx, and nomogram. Further analyses included pan-cancer, mutation, GSEA, immune infiltration, single-cell, TF regulation, and drug-target association (DrugBank).

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